1. Field of the Invention
The present invention relates to a wireless localization method based on a wireless sensor network, more specifically to a wireless localization method, which is able to correct localization error precisely in real time in a wireless localization through multilateration algorithm using received signal strength indicator (RSSI). Here, the term ‘multilateration’ is a concept including trilateralism and indicates a method for estimating an estimated location of a blind node using more than three reference nodes.
2. Background Art
As the interest on smart phones increases explosively, a location based service (LBS) receives spotlight, and for example, location-recognizing applications such as augmented reality, medical care, home network, monitoring applications, etc. are popular. For such a LBS, a localization on location of user requesting the service must be achieved precisely.
A well-known localization system includes a global positioning system (GPS) with applications used as mobile navigation. However, the GPS provides a high performance in an outdoor environment, but since the location information is obtained using satellites there is a limit in that it is hard to achieve a precise localization indoors. Therefore, the GPS is not suitable for a localization system in indoor channel environments or with low-cost devices.
For such reasons, for indoor wireless localization, technologies such as wireless local area network (WLAN), ultra wide band (UWB) communication, and wireless sensor network (WSN) have been suggested and many researches have been performed. The WLAN or UWB system has various limits to cost, battery, size of system device, etc. On the contrary, the WSN is a method which provides many sensor nodes of small size and uses them for localization, and has advantages such as low cost, easy installation, small size, and possibility of connecting numerous nodes. The indoor environment has many obstacles such as wall, door, pillar, etc, and especially when there are objects of metal, the strength of received signal shows a very large difference according to whether it is an environment of line-of-sight (LOS) or non-line-of-sight (NLOS). The WSN can make such environmental factors optimal by forming tree topology network. Since it can connect many nodes, it is possible to form a network avoiding walls between rooms. Due to such features, the WSN is estimated as a very useful system in indoor channel environment. Zigbee technology is a close-range wireless communication technology of low cost, low power-consumption, and low speed based on IEEE 802.15.4. Since the node device applied with the Zigbee technology may have a very simple hardware structure and can be connected to many other nodes in a network, it is possible to form a WSN of very low cost effectively using them.
On the other hand, well-known representative wireless localization methods include a range free approach and a range based approach. A method for estimating a location without information on the distance between transmitter side and receiver side in estimating the location of a user is the range free approach, but since the method requires a high cost and has to store enormous amount of information, its real feasibility is low. On the contrary, the range based approach is a method for estimating location based on information on distance between transmitter side and receiver side, and includes trilateration estimation, least square estimation (LSE), weight least square estimation (WLSE), etc.
A representative method for estimating the distance between transmitter side and receiver side, which is used in the range based approach, is a method using RSSI. The RSSI method uses a model of path-loss of signal for estimating the distance between transmitter side and receiver side using strength of signal received at the receiver side only. This method is simple because it does not use a complicated method such as synchronization of the transmitter side and receiver side, but the property of the signal makes the accuracy decreased in a region where NLOS is formed. However, in case of using a low-cost node such as Zigbee, if making a network by positioning many sensor nodes in a narrow region, it is possible to make an environment where each node forms a LOS. If making a network of tree topology as in FIG. 1 using such environmental factors, it is possible to make an environment optimal for estimating location using the RSSI indoors.
The trilateration is widely used as a basic method for estimating location of user using the distance between transmitter side and receiver side which is estimated by a method using RSSI. For a precise localization using trilateration, it is necessary to set a center on a node (‘reference node’) the location of which is known, such that three circles with distances estimated by RSSI as radii form cross lines and such cross lines form a single cross point (see FIG. 2). However, if there is a large error in estimating the distance between transmitter side and receiver side, the distance is estimated too large or too small, such that one circle may be separated from the other circle(s) or one circle may include the other circle(s) completely, that is, an occasion that the three circles are not able to form cross lines (see FIG. 3) may occur in real situation. When one circle is separated completely from the other circle(s) or includes the other circle(s) completely, the estimation error gets relatively larger than otherwise. Therefore, the trilateration based on RSSI needs to seek a method for improving such a localization error fundamentally.
In order to correct the localization error in prior arts, prior to calculating estimated location using trilateration, correcting of error in estimated distance obtained using RSSI was performed first, and then the estimated location was obtained with trilateration using the error-corrected estimated distance. Since the estimated distance used in trilateration was error-corrected, another error-correction to the estimated distance obtained in trilateration was not performed further, and it was determined as a final estimated location to be obtained. However, since such conventional wireless localization method based on error-correction of estimated distance has an algorithm of complicated and recursive calculations and the amount of calculations increases further to increase accuracy of localization, it is not suitable to the real-time wireless localization service.
Since the wireless localization approach according to the conventional WLSE determines a correction using as channel factors such as channel exponent and a size of log-normal shadowing, there is a limit to it. For it is very hard to know precisely two channel factors. Therefore, it does not become a practical method.